Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.526064
Title: Novel source coding methods for optimising real time video codecs
Author: Elangovan, Premkumar
ISNI:       0000 0004 2691 9031
Awarding Body: Brunel University
Current Institution: Bucks New University
Date of Award: 2009
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Abstract:
The quality of the decoded video is affected by errors occurring in the various layers of the protocol stack. In this thesis, disjoint errors occurring in different layers of the protocol stack are investigated with the primary objective of demonstrating the flexibility of the source coding layer. In the first part of the thesis, the errors occurring in the editing layer, due to the coexistence of different video standards in the broadcast market, are addressed. The problems investigated are ‘Field Reversal’ and ‘Mixed Pulldown’. Field Reversal is caused when the interlaced video fields are not shown in the same order as they were captured. This results in a shaky video display, as the fields are not displayed in chronological order. Additionally, Mixed Pulldown occurs when the video frame-rate is up-sampled and down-sampled, when digitised film material is being standardised to suit standard televisions. Novel image processing algorithms are proposed to solve these problems from the source coding layer. In the second part of the thesis, the errors occurring in the transmission layer due to data corruption are addressed. The usage of block level source error-resilient methods over bit level channel coding methods are investigated and improvements are suggested. The secondary objective of the thesis is to optimise the proposed algorithm’s architecture for real-time implementation, since the problems are of a commercial nature. The Field Reversal and Mixed Pulldown algorithms were tested in real time at MTV (Music Television) and are made available commercially through ‘Cerify’, a Linux-based media testing box manufactured by Tektronix Plc. The channel error-resilient algorithms were tested in a laboratory environment using Matlab and performance improvements are obtained.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.526064  DOI: Not available
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